The Cloud-to-ground (CG) lightning causes nearly a billion dollars of property damage and approximately 90 fatalities per year in the United States, second only to flooding. Yet the lightning warning facilities as implemented are minimal at best. On military bases, where lightning strikes can have a devastating effect if a munitions depot is struck, base-wide warnings are issued if lightning strikes are observed with 5 miles of the base. Some amateur athletic associations also require lightning detectors for athletic contests; detections result in delayed games while participants and fans clear the field. These warnings do not go out to the general public who may have no knowledge of impending lightning threats. In addition, this system relies on previous strikes within the area and therefore the potential before a strike is unknown.
A significant source of lightning concern is sporting activities that are played in open areas such as baseball, softball, football, soccer, and golf. In 1997, NOAA conducted a study of 3,239 lightning deaths over 35 years. They found that five times more people are killed by lightning in open fields or parks. Playgrounds and parks accounted for nearly 27% of lightning deaths, and golfers accounted for only 5% of deaths during the period.
There are two categories of devices that seek to provide a prediction capability of lightning threat, systems that predict lightning threat based upon a history of strikes and those that predict lightning threat before or independent of any strikes. The former typically utilize radiofrequency (RF) sensors to detect and characterize the electromagnetic pulse created by the lightning discharge. The latter attempt to forecast lightning threat based upon the atmospheric conditions measured through a variety of sensors including, but not limited to, electric field sensors, radar, radiosonde, radiometers, satellite, sodar, and weather stations sensors. The present invention relates to this category of devices.
Post-strike sensors detect the electromagnetic pulse resulting from the lightning discharge and associate the pulse characteristics with the lightning. The devices range in size from a hand held device that estimates range based upon an amplitude threshold to large, distributed networks of sensors that receive the energy from the lightning pulse at different times and perform time of arrival calculations to determine location. Many of these sensors detect the transient variations in magnetic field resulting from the pulse. These sensors however are very sensitive to metallic structures and other magnetic anomalies, thereby reducing their reliability. Electric field sensors are more susceptible to noise and thus require significant bandpass filtering to ensure detection.
Prestrike prediction uses knowledge of the atmospheric conditions to forecast lightning threat. These systems are useful in that they can make a forecast before the first strike. Electric field sensors such as the E-field mill sensor measure the static background electric field. As charge separation occurs within the cloud, the electric field within the cloud and between the cloud and ground increases. Once the electric field reaches a particular threshold, called the breakdown threshold, discharge may occur. So, the electric field sensors measure the magnitude of the electric field at the ground in the hopes that a significant electric field is enough to forecast lightning. Unfortunately, electric field values alone are insufficient to forecast lightning.
Obtaining soundings of the atmosphere has been the standard technique of obtaining measurements of atmospheric parameters of different altitudes. These measurements are obtained by releasing a high altitude balloon with an instrument package called a radiosonde. The radiosonde transmits the measurements (hence the radio) to a base station. These profiles are obtained at stations throughout the country twice a day at 0000 UTC and 1200 UTC. The profiles are the atmospheric parameters measured as a function of altitude and include quantities such as temperature, pressure, humidity, dew point, mixing ratio, wind speed and direction. One value determined from these parameters is called the convective available potential energy (CAPE). The CAPE is related to how quickly storms will develop vertically. A very high CAPE indicates highly unstable air and a significant potential for storm development and lightning. Unfortunately, like many atmospheric parameters, the interpretation of the CAPE is very dependent upon a region's underlying climate.
With the advent of digital processing of radar data in the 1980's, meteorological radar products greatly enhanced the ability of the world's meteorological services to provide warnings of severe weather conditions associated with convective cells. This includes but is not limited to tornados, wind shear, microbursts, gust fronts, hail, and lightning. The weather radar performs a number of surveillance scans in 360 degrees of azimuth at different elevations. Each set of elevation scans is considered a volume. The radar products are the result of computer-processing of this volumetric data. For lightning forecasting typical modules considered used the Echo Tops (ETOPS) and Vertically Integrated Liquid (VIL) products as proxies for lightning potential. The ETOPS product is the maximum height observed for reflectivities (signal powers) above a certain threshold. The VIL product is the integration of liquid water content (related to the reflectivity) in a vertical column. The ETOPS products give a measure of the strength of the convection. The higher in the atmosphere the reflectivity the stronger the convection and hence the greater likelihood of lightning. The VIL gives a measure of the potential energy in the atmosphere. The greater the VIL, the more water content and hence the more potential energy available for lightning to develop. Both these products by themselves or together with no additional information provide a good measure of the lightning threat level at very high flash rates but are ineffective for low flash rates, i.e. as the storm is developing.
Adding supplementary information about the atmosphere to the radar product generation greatly enhances the ability to forecast lightning. In particular the altitude at which ice crystals form, e.g. the −10° C. level, compared to the ETOPS with a threshold of 40 dBZ is related to the likelihood of cloud-to-ground lightning Wolf empirically determined probability density functions for the cloud-to-ground lightning threat (see Wolf, P., 2007: Anticipating the Initiation, Cessation, and Frequency of Cloud-to-Ground Lightning, Utilizing WSR-88D Reflectivity Data, National Weather Association, http://www.nwas.org/ej/2007/2007.php). Stagliano implemented the module and showed that if such a product was available on Sep. 11, 2008 the initial discharge from a convective cell could have been forecast and a middle school football field that was struck could have been cleared in time (see Stagliano, J., B. Valant-Spaight, J. C. Kerce, 2009: “Lightning Forecasting Before The First Strike”, 4th Symposium on Meteorological Uses of Lightning Data, 11-15 January, Phoenix, Ariz.).
The techniques described by Wolf and implemented by Stagliano require knowledge external from the radar which is typically found through soundings that are spatially and temporally sparse. The availability and sparseness of this data limits the functionality of the module.